Bo Pieter Johannes Andree

World Bank · Development Economics Data Group

The UN's Sustainable Development Goals for 2030 aim on one hand at inclusive growth and eradicating poverty, and on the other at preserving environments. The relation between development and the environment has been studied extensively since the 1990s, documenting inverted U-shaped relations between per capita income and indicators of environmental...

Stochastic economic processes are often characterized by dynamic interactions between variables that are dependent in both space and time. Analyzing these processes raises a number of questions about the econometric methods used that are both practically and theoretically interesting. This work studies econometric approaches to analyze spatial data...

Globally, more than 130 million people are estimated to be in food crisis. These humanitarian disasters are associated with severe impacts on livelihoods that can reverse years of development gains. The existing outlooks of crisis-affected populations rely on expert assessment of evidence and are limited in their temporal frequency and ability to l...

High resolution models are essential to assess the localised impacts of global environmental change. To enable the estimation of the impacts of location-specific change, this paper presents a new modelling approach that disaggregates scenario-based national-level urban population estimates derived from the often-applied Shared Socioeconomic Pathway...

Growth is forecasted to slow down for the Middle East and North Africa region. The war in Ukraine in 2022 exacerbated inflationary pressures as the world recovered from the COVID 19 pandemic induced recession. The response by central banks to raise rates to curb inflation is slowing economic activity, while rising food prices are making it difficul...

Capabilities to track fast-moving economic developments remain limited in many regions of the developing world. This complicates prioritizing policies aimed at supporting vulnerable populations. To gain insight into the evolution of fluid events in a data scarce context, this paper explores the ability of recent machine-learning advances to produce...

The present Special Issue of Entropy, entitled "Causal Inference for Heterogeneous Data and Information Theory", covers various aspects of causal inference. The issue presents thirteen original contributions that span various topics, namely the role of instrumental variables in causal inference, the estimation of average treatment effects and the t...

Why are certain labour markets more resilient to economic shocks? Why are some economies deeply affected by migration? Modern migration theory remains based on simplistic neo-classical utility maximizing assumptions, despite a failure to fully answer real-world migration questions. The aim of this paper is to show that neo-classical dynamics are di...

Motivated by the deterioration in global food security conditions, this paper develops a parsimonious machine learning model to derive a multi-year outlook of global severe food insecurity from macro-economic projections. The objective is to provide forecasts that are internally consistent with wider economic assessments, allowing both food securit...

Recent advances in food insecurity classification have made analytical approaches to predict and inform response to food crises possible. This paper develops a predictive, statistical framework to identify drivers of food insecurity risk with simulation capabilities for scenario analyses, risk assessment and forecasting purposes. It utilizes a pane...

The traditional consumer price index is often produced at an aggregate level, using data from few, highly urbanized, areas. As such, it poorly describes price trends in rural or poverty-stricken areas, where large populations may reside in fragile situations. Traditional price data collection also follows a deliberate sampling and measurement proce...

This dataset is part of a series of frequently-updated data files providing monthly food prices and inflation estimates for a series of fragile countries. See https://microdata.worldbank.org/index.php/catalog/4491 for current.

This dataset is part of a series of frequently-updated data files providing monthly food prices and inflation estimates for a series of fragile countries. Monthly food price estimates by product and market, 01/2007 to 01/2022 (25 Fragile & Conflicted countries; 1225 markets), Version 2022-01-20 See https://microdata.worldbank.org/index.php/catal...

The current paper develops a probabilistic theory of causation using measure-theoretical concepts and suggests practical routines for conducting causal inference. The theory is applicable to both linear and high-dimensional nonlinear models. An example is provided using random forest regressions and daily data on yield spreads. The application test...

The 2UP model was developed by PBL Netherlands Environmental Assessment Agency for spatially explicit simulation of the future growth of cities and population at a global scale (van Huijstee et al., 2018). The model describes urban land use and population at a fine 30” spatial resolution equivalent to approximately 1x1km near the equator. The model...

The traditional consumer price index is often produced at an aggregate level, using data from few, highly urbanized, areas. As such, it poorly describes price trends in rural or poverty-stricken areas, where large populations may reside in fragile situations. Traditional price data collection also follows a deliberate sampling and measurement proce...

For this study, predictive modelling is used to validate a high-resolution model that simulates urban development. A logit model is used to predict the likelihood of a cell being classified as urban or non- urban based on historical data. Several essential choices had to be made during the validation process about the classification model and the m...

The South Sudan economy is projected to contract by 4.1 percent in FY2020/21, with growth negatively affected by the impact of the COVID-19 pandemic, lower oil production, floods, and increased conflict intensity in parts of the country. With the economic decline in FY2020/21, living conditions have deteriorated, with some 8.3 million estimated to...

While conflicts and violence have precipitated food insecurity in South Sudan since 2013, the influence of conflict on food systems has occurred mainly through secondary channels including displacement and decreased crop production and market access. Displacement has disrupted harvest and growing cycles, and in many areas, has caused farmers to wor...

Recent advances in food insecurity classification have made analytical approaches to predict and inform response to food crises possible. This paper develops a predictive, statistical framework to identify drivers of food insecurity risk with simulation capabilities for scenario analyses, risk assessment and forecasting purposes. It utilizes a pane...

Understanding how COVID-19 infections evolve spatially as well as over time can help countries more effectively confront the ongoing pandemic. Air pollution is a key mediator: people living in areas with higher levels of air pollution face a greater risk of infection and of suffering more severe infection. Two factors are at play: (1) preexisting p...

The fast spread of severe acute respiratory syndrome coronavirus 2 has resulted in the emergence of several hot-spots around the world. Several of these are located in areas associated with high levels of air pollution. This study investigates the relationship between exposure to particulate matter and COVID-19 incidence in 355 municipalities in th...

The fast spread of severe acute respiratory syndrome coronavirus 2 has resulted in the emergence of several hot-spots around the world. Several of these are located in areas associated with high levels of air pollution. This study investigates the relationship between exposure to particulate matter and COVID-19 incidence in 355 municipalities in th...

The fast spread of severe acute respiratory syndrome coronavirus 2 has resulted in the emergence of several hot-spots around the world. Several of these are located in areas associated with high levels of air pollution. This study investigates the relationship between exposure to particulate matter and COVID-19 incidence in 355 municipalities in th...

Future population growth is expected to concentrate in urban agglomerations that are already exposed to numerous natural hazards. It is difficult, however, to assess this increase in risk as natural hazards are often concentrated in space and population growth scenarios tend to be defined at much coarser scales. By combining recently released high-...

The current paper discusses approximating a correct theory of cause and effect by minimizing distance to its associated probability measure in a space of measures in which each element is associated with a stochastic representation of a candidate theory. The discussion encourages researchers to use flexible dynamical models to model and discover th...

This paper revisits the issue of environment and development raised in the 1992 World Development Report, with new analysis tools and data. The paper discusses inference and interpretation in a machine learning framework. The results suggest that production gradually favors conserving the earth's resources as gross domestic product increases, but i...

This paper introduces a Spatial Vector Autoregressive Moving Average (SVARMA) model in which multiple cross-sectional time series are modeled as multivariate, possibly fat-tailed, spatial autoregressive ARMA processes. The estimation requires specifying the cross-sectional spillover channels through spatial weights matrices. the paper explores a ke...

De toenemende beschikbaarheid van nieuwe (big) databronnen en data sciences methoden opent mogelijkheden om op een alternatieve manier verplaatsingsgedrag in termen van herkomst en bestemming, verplaatsingsmotief en routekeuze te analyseren. Dit onderzoeksproject heeft verkend in hoeverre het mogelijk is om floating car data te gebruiken om analyse...

This chapter provides a detailed review of the sources of data used in the impact estimates of road development on the welfare of poor households. This is intended to guide future researchers and encourage similar studies. Using administrative road inventory data combined with repeated cross-sectional household survey data (including the geographic...

The 2UP model – to an Urban Preview – is developed for the spatially explicit simulation of the future growth of cities and population at a global scale. The model describes urban land use at a fine 30” spatial resolution (approx. 1km near the equator). In the current version of the model, the allocation of urban land use is mainly based on current...

These are the slides I used for the blockchain introduction talk I gave on the 4th of December in the Preston Auditorium - World Bank, Washington D.C. Due to the many requests for the slides I received, I decided to upload these here.

We propose a method that combines local productivity factors, economic factors, crop-specific sensitivity to climatic extremes, and future climate change scenarios, to assess potential impacts of extreme weather events on agricultural production systems. Our assessment is spatially explicit and uses discounted time series of cash flows taking into...

Policy schemes that aim to stimulate the cultivation of biofuel crops typically ignore the spatial het-erogeneity in costs and benefits associated with their production. Because of spatial heterogeneity in biophysical, and current agricultural production factors, potential gains from stimulating biofuel crops are non-uniformly distributed across sp...

This paper introduces a new model for spatial time series in which cross-sectional dependence varies nonlinearly over space by means of smooth transitions. We refer to our model as the Smooth Transition Spatial Autoregressive (ST-SAR). We establish consistency and asymptotic Gaussianity for the MLE under misspecification and provide additional cond...